Image Space Rendering of Point Clouds Using the HPR Operator

The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as th...

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Bibliographic Details
Published in:	Computer graphics forum Vol. 33; no. 1; pp. 178 - 189
Main Authors:	Machado e Silva, R., Esperança, C., Marroquim, R., Oliveira, A. A. F.
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.02.2014
Subjects:	I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling-Geometric algorithms languages and systems surface reconstruction rendering visibility determination
ISSN:	0167-7055, 1467-8659
Online Access:	Get full text
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Summary:	The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real‐time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy. The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real‐time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy.
Bibliography:	ark:/67375/WNG-Q66H0DRS-7 istex:7019D1BC020161777B01112051F4962535DC6EAD ArticleID:CGF12265 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0167-7055 1467-8659
DOI:	10.1111/cgf.12265